• 제목/요약/키워드: adaptive filtering

검색결과 509건 처리시간 0.027초

Complexity Reduction of an Adaptive Loop Filter Based on Local Homogeneity

  • Li, Xiang;Ahn, Yongjo;Sim, Donggyu
    • IEIE Transactions on Smart Processing and Computing
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    • 제6권2호
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    • pp.93-101
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    • 2017
  • This paper proposes an algorithm for adaptive loop filter (ALF) complexity reduction in the decoding process. In the original ALF algorithm, filtering for I frames is performed in the frame unit, and thus, all of the pixels in a frame are filtered if the current frame is an I frame. The proposed algorithm is designed on top of the local gradient calculation. On both the encoder side and the decoder side, homogeneous areas are checked and skipped in the filtering process, and the filter coefficient calculation is only performed in the inhomogeneous areas. The proposed algorithm is implemented in Joint Exploration Model (JEM) version 3.0 future video coding reference software. The proposed algorithm is applied for frame-level filtering and intra configuration. Compared with the JEM 3.0 anchor, the proposed algorithm has 0.31%, 0.76% and 0.73% bit rate loss for luma (Y) and chroma (U and V), respectively, with about an 8% decrease in decoding time.

적응비선형 필터링과 전략적 채략이동 목표물의 추적에 관하여 (On Nonlinear Adaptive Filtering and Maneuvering Target Tracking)

  • 이만형;김종화
    • 대한전기학회논문지
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    • 제36권12호
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    • pp.908-917
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    • 1987
  • Most of moving targets are modelled as nonlinear dynamic equations. In recent years, the extended Kalman filter is frequently used for estimating their behaviors. The conditional Gaussian filter is more suitable than extended kalman filter in the filtering problem of nonlinear systems. But extended Kalman filter and conditional Gaussian filter often do not give optimal estimates and fail to track target trajectories because of its properties. Therefore it is desirable to use adaptive techniques to adapt target maneuvers. In this paper, we will discuss adaptive filtering technique using innovation process based on extended Kalman filter in real time, and suggest another maneuver estimation method using MRAS technique.

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FBEGS-PAP 알고리즘 기반 볼테라 필터링을 이용한 비선형 반향신호 제거 (Nonlinear echo cancellation using FBEGS-PAP based Volterra filtering)

  • 서재범;김경재;남상원
    • 전기학회논문지
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    • 제56권2호
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    • pp.420-423
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    • 2007
  • In this paper, an efficient nonlinear echo cancellation method is proposed, whereby the fast block exact Gauss-Seidel pseudo affine projection (FBEGS-PAP) is further utilized for adaptive Volterra filtering. In particular, the proposed nonlinear echo cancellation approach requires lower computational complexity as in the conventional linear adaptive echo cancellation methods based on NLMS and GS-PAP, and still provides nonlinear echo cancellation performance similar to the GS-PAP method. Finally, echo cancellation performance of the proposed approach is demonstrated by providing some simulation results.

Adaptive Filtering Scheme for Defense of Energy Consumption Attacks against Wireless Computing Devices

  • Lee, Wan Yeon
    • International journal of advanced smart convergence
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    • 제7권3호
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    • pp.101-109
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    • 2018
  • In this paper, we propose an adaptive filtering scheme of connection requests for the defense of malicious energy consumption attacks against wireless computing devices with limited energy budget. The energy consumption attack tries to consume the battery energy of a wireless device with repeated connection requests and shut down the wireless device by exhausting its energy budget. The proposed scheme blocks a connection request of the energy consumption attack in the middle, if the same connection request is repeated and its request result is failed continuously. In order to avoid the blocking of innocuous mistakes of normal users, the scheme gives another chance to allow connection request after a fixed blocking time. The scheme changes the blocking time adaptively by comparing the message arriving ate during non-blocking period and that during blocking period. Evaluation shows that the proposed defense scheme saves up to 94% energy consumption compared to the non-defense case.

국부 통계를 이용한 메디안 필터의 적응 영상 복원 (Adaptive Image Restoration of Median Filter Using Local Statistics)

  • 김남철;윤장홍;황찬식
    • 대한전자공학회논문지
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    • 제24권5호
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    • pp.863-867
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    • 1987
  • When digital image signals are transmitted or stored, they may be usually degraded by impulsive noise such as BSC noise. Though median filtering is a very effective method to reduce the impulsive noise, it brings non-negligible distortion after filtering. Several algorithms have been proposed to reduce such a distortion, but their reconstructed image quality are inadequate in some cases and they have a difficulty in real-time processing. In this paper, an effective filtering algorithm which can not only reduce the noise effectively but also preserve the edges well and lessen the distortion greatly, is presented. The proposed algorithm is an adaptive algorithm of median filter using local statistics, based on the characteristics of human eyes. The adaptive algorithm results shwo performance improvement of up to 3-4 dB over the nonadaptive one.

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Adaptive Kalman Filter Design for an Alignment System with Unknown Sway Disturbance

  • Kim, Jong-Kwon;Woo, Gui-Aee;Cho, Kyeum-Rae
    • International Journal of Aeronautical and Space Sciences
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    • 제3권1호
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    • pp.86-94
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    • 2002
  • The initial alignment of inertial platform for navigation system was considered. An adaptive filtering technique is developed for the system with unknown and varying sway disturbance. It is assumed that the random sway motion is the second order ARMA(Auto Regressive Moving Average) model and performed parameter identification for unknown parameters. Designed adaptive filter contain both a Kalman filter and a self-tuning filter. This filtering system can automatically adapt to varying environmental conditions. To verify the robustness of the filtering system, the computer simulation was performed with unknown and varying sway disturbance.

ADAPTIVE CONTROL USING NEURAL NETWORK FOR MINIMUM-PHASE STOCHASTIC NONLINEAR SYSTEM

  • Seok, Jinwuk
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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    • pp.18-18
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    • 2000
  • In this paper, some geometric condition for a stochastic nonlinear system and an adaptive control method for minimum-phase stochastic nonlinear system using neural network are provided. The state feedback linearization is widely used technique for excluding nonlinear terms in nonlinear system. However, in the stochastic environment, even if the minimum phase linear system derived by the feedback linearization is not sufficient to be controlled robustly. the viewpoint of that, it is necessary to make an additional condition for observation of nonlinear stochastic system, called perfect filtering condition. In addition, on the above stochastic nonlinear observation condition, I propose an adaptive control law using neural network. Computer simulation shows that the stochastic nonlinear system satisfying perfect filtering condition is controllable and the proposed neural adaptive controller is more efficient than the conventional adaptive controller

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VLSI Implementation for the MPDSAP Adaptive Filter

  • Choi, Hun;Kim, Young-Min;Ha, Hong-Gon
    • 융합신호처리학회논문지
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    • 제11권3호
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    • pp.238-243
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    • 2010
  • A new implementation method for MPDSAP(Maximally Polyphase Decomposed Subband Affine Projection) adaptive filter is proposed. The affine projection(AP) adaptive filter achieves fast convergence speed, however, its implementation is so expensive because of the matrix inversion for a weight-updating of adaptive filter. The maximally polyphase decomposed subband filtering allows the AP adaptive filter to avoid the matrix inversion, moreover, by using a pipelining technique, the simple subband structured AP is suitable for VLSI implementations concerning throughput, power dissipation and area. Computer simulations are presented to verify the performance of the proposed algorithm.

Design of an Adaptive Filter with a Dynamic Structure for ECG Signal Processing

  • Lee Ju-Won;Lee Gun-Ki
    • International Journal of Control, Automation, and Systems
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    • 제3권1호
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    • pp.137-142
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    • 2005
  • Biomedical signals such as ECG, EMG, and EEG are extremely important in the diagnosis of patients. It is difficult to filter noise from these signals, and errors resulting from filtering can distort a biomedical signal. Existing systems have shown poor performance when complicated noise appears. Adaptive filtering is selected to contend with these defects. Existing adaptive filters can adjust the filter coefficient with the given filter order, but they can produce an unsuitable order in different environments. In order to solve this problem, an optimal adaptive filter with a dynamic structure was designed. Positive experimental results were obtained.

SAP 잡음 제거를 위한 적응적 스위칭 필터링 알고리즘 (Adaptive Switching Filtering Algorithm for SAP noise)

  • 김동형
    • 디지털산업정보학회논문지
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    • 제18권1호
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    • pp.25-35
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    • 2022
  • The SAP(salt-and-pepper) noise changes the pixel value to the maximum and minimum values of the dynamic region of the pixel. For this reason, unlike white Gaussian noise, SAP noise can predict the ratio of noise relatively easily. Because the condition of the neighboring pixels that can be referenced changes according to the noise ratio, it is necessary to apply different noise reduction methods according to the noise ratio. This paper proposes an adaptive switching filtering algorithm which can eliminates the SAP noise. It consists of two phases. It first detects the location of the SAP noise and calculates the noise ratio. After that, the image is reconstructed using different methods depending on which of the three sections the calculated noise ratio belongs to. As a result of the experiment, the proposed method showed superior objective and subjective image quality compared to the previous methods such as MF, AFSWMF, NAMF and RWMF.